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dparra19/dparcon

sourceHugging Faceapache-2.0updated 2mo agoView on Hugging Face
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Model Card

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dparcon

This model is a fine-tuned version of gplsi/Aitana-2B-S-base on the dataset showed in my account (descriptions about fruits and vegetables). It achieves the following results on the evaluation set:

  • —Loss: 1.8984

Model description

The gplsi/Aitana-2B-S-base consists on a generative language model on multilingual data (Spanish, Valencian and English). In this case, we have fine-tuning this model to answer information about certain fruits and vegetables.

Intended uses & limitations

More information needed

Training and evaluation data

We have used the following dataset

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • —learning_rate: 0.0002
  • —trainbatchsize: 4
  • —evalbatchsize: 4
  • —seed: 42
  • —gradientaccumulationsteps: 4
  • —totaltrainbatch_size: 16
  • —optimizer: Use OptimizerNames.PAGEDADAMW8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 2
  • —num_epochs: 10
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation Loss
2.14051.032.1311
2.06582.062.0559
1.95343.092.0014
1.89234.0121.9646
1.83915.0151.9432
1.73746.0181.9290
1.71357.0211.9172
1.67008.0241.9076
1.66439.0271.9014
1.664710.0301.8984

Framework versions

  • —PEFT 0.19.1
  • —Transformers 5.14.1
  • —Pytorch 2.11.0+cu128
  • —Datasets 5.0.0
  • —Tokenizers 0.22.2